During this part of the research, we will analyze what the different stages of maturity are in the creation of smart factories. At the same time, we want to delve deeper into the possible measures that companies can adopt to overcome the step to becoming Digital Masters. The real goal of Industry 4.0 is to build digital companies from the point of view of the business model and the production process. To analyze the state of the art of each company, the research took into consideration two different variables, first of all the level of digital application and integration, secondly the change management for the transition from automated production to the digital factory. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essayDigital Intensity, the “what,” illustrates the extent to which essential processes, such as manufacturing, inventory management, quality, planning and forecasting, have been digitized and how much use is being made of digital technologies such as robotics, the Internet of Things , artificial intelligence, big data analytics, CPPS and so on. The intensity of transformation management, the “how,” illustrates how well the transformation is managed to generate benefits, including key aspects such as the manufacturer's smart factory vision, governance and the digital skills of its workforce. Finally, we can conclude that the digital Masters detected during the research are only 4% in the automotive industry sector. It is composed of companies that score high in both dimensions of digital management intensity and transformation. They are at an advanced stage in the digitalization of production processes and have a solid foundation of vision, governance and employee skills. Let's go back to Capgemini's latest research on the automotive sector in 2018. It is the digital maturity of manufacturers that holds the key to reaching full potential. During the study, manufacturers were divided into three categories: struggling, early stage and making good progress. Below, we'll explore how each of the three categories can graduate to become "digital masters." By “masters” we mean organizations that have digitally mature manufacturing operations and consistently achieve greater operational revenue and financial benefits. Summing up from the figure above we can conclude that people in difficulty need a clear vision, strong investments and a focus on the features used by digital masters. The lack of vision is significant. The research estimated that around two-thirds of “struggling” organizations admit they do not have a clear vision for their smart factories. This means they underestimate key elements, such as the disruptive power of smart factories or the ongoing investments required. The most effective way to develop a clear vision is to connect it to the strategic objectives of the organization. For example, Faurecia, one of the world's leading automotive suppliers, has identified five strategic initiatives: paperless manufacturing, artificial intelligence, increased automation, improved traceability and logistics optimization to develop its smart factory vision. In addition to a lack of vision, struggling companies often fail to identify the smart factory features and technologies used by digital masters. For example, as we saw in the second chapter, production analytics and predictive maintenance through the adoption of cyber physical production system are two of the most crucial features of smart factories, as they help improvequality, costs and productivity performance. In fact, the survey finds that more than 80% of digital masters leverage production analytics and approximately two-thirds implement predictive maintenance. However, only about 30% of struggling companies say they would implement predictive maintenance, and fewer than 40% say the same for production analytics. Possible solutions to this problem can be the adoption of roadmap definition and business case analysis, which are considered effective means to identify appropriate features and technologies. Considered as the main part is that struggling organizations need to ensure that their smart factory initiatives do not suffer from lack of investment. In fact, digital masters have invested more than $1 billion on average over the past five years, compared to average investments of $380 million made by struggling organizations. The investment gap between digital masters and struggling companies can be easily spotted and is due to a lack of clarity on a vision and an inability to find compelling business cases. It may be considered a good idea to launch a pilot project that can demonstrate the potential added value. Now we will focus on the early stagers and what are the points they need to work on. Automakers that are in an early stage of their smart factory initiative are doing better on several fronts, such as developing a smart factory vision and identifying crucial smart factory characteristics than companies that are struggling . However, governance is one area where they need to improve significantly. Effective governance begins with appointing a leader and forming a committee to guide decision-making and prioritize actions. In fact, it is considered of primary importance to appoint a leader for smart factory initiatives, the leader must coordinate with the different units of the organization to understand the next steps and what the best strategy would be. As can be seen from the survey data, nearly 100% of digital masters have appointed a leader for their smart factory strategy and formed a decision-making committee. However, more than half of automotive companies with early-stage smart factory projects have yet to do the same. As we saw in the first chapter, one of the most important factors for successful adoption of Industry 4.0 is building a talent pool. of workers. The success of early-stage companies depends largely on how effectively they scale their initiatives from the pilot level to the industrial level. To grow, you need employees with digital skills. Survey data tells us that a lack of digital skills can become a major obstacle. Less than 20% of early-stage companies believe they have adequate skills in areas such as cyber-physical systems and data analytics. But 50% of digital masters do. Additionally, the study reveals how early stagers acquire qualified employees. They usually improve the skills of the existing talent pool, but as we can see from the digital master, external hiring for very specialized areas is also important and fundamental. Finally, early-stage organizations are more likely to adopt industry-specific technology solutions, such as collaborative robots and intelligent systems. display, rather than the end-to-end transformation of manufacturing operations. The survey shows that 66% of participants were implementing timely technology solutions at the beginning of the implementation phase, while only 32% of respondents opted for a.